Instance Segmentation

Instance Segmentation is a computer vision task that involves identifying and separating individual objects within an image, including detecting the boundaries of each object and assigning a unique label to each object. The goal of instance segmentation is to produce a pixel-wise segmentation map of the image, where each pixel is assigned to a specific object instance.

Image Credit: Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers, CVPR'21

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1831–1840 of 2262 papers

Title	Date	Tasks	Status	Hype
Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation	May 7, 2020	ClusteringGPU	CodeCode Available	1
Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-weighting	May 5, 2020	Domain AdaptationInstance Segmentation	CodeCode Available	1
Counting of Grapevine Berries in Images via Semantic Segmentation using Convolutional Neural Networks	Apr 29, 2020	Instance SegmentationSemantic Segmentation	—Unverified	0
A novel Region of Interest Extraction Layer for Instance Segmentation	Apr 28, 2020	Instance Segmentationobject-detection	CodeCode Available	0
Dynamic Scale Training for Object Detection	Apr 26, 2020	Instance SegmentationModel Optimization	CodeCode Available	1
All you need is a second look: Towards Tighter Arbitrary shape text detection	Apr 26, 2020	AllInstance Segmentation	—Unverified	0
Fashionpedia: Ontology, Segmentation, and an Attribute Localization Dataset	Apr 26, 2020	AttributeFine-Grained Visual Categorization	CodeCode Available	1
Instance Segmentation of Biomedical Images with an Object-aware Embedding Learned with Local Constraints	Apr 21, 2020	Cell SegmentationInstance Segmentation	CodeCode Available	1
ResNeSt: Split-Attention Networks	Apr 19, 2020	image-classificationImage Classification	CodeCode Available	3
MOPT: Multi-Object Panoptic Tracking	Apr 17, 2020	Instance SegmentationMulti-Object Tracking	—Unverified	0

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All datasets COCO test-dev COCO minival LVIS v1.0 val Cityscapes val ADE20K val ARMBench Occluded COCO OoDIS Separated COCO TBBR BDD100K val COCO val (panoptic labels)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	InternImage-H	AP50	80.8	—	Unverified
2	ResNeSt-200 (multi-scale)	AP50	70.2	—	Unverified
3	CenterMask + VoVNetV2-99 (multi-scale)	AP50	66.2	—	Unverified
4	CenterMask + VoVNetV2-57 (single-scale)	AP50	60.8	—	Unverified
5	Co-DETR	mask AP	57.1	—	Unverified
6	CBNetV2 (EVA02, single-scale)	mask AP	56.1	—	Unverified
7	ISDA (ResNet-50)	APL	55.7	—	Unverified
8	EVA	mask AP	55.5	—	Unverified
9	FD-SwinV2-G	mask AP	55.4	—	Unverified
10	Mask Frozen-DETR	mask AP	55.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	InternImage-B	GFLOPs	501	—	Unverified
2	Co-DETR	mask AP	56.6	—	Unverified
3	ViT-CoMer-L (Mask RCNN, DINOv2)	mask AP	55.9	—	Unverified
4	InternImage-H	mask AP	55.4	—	Unverified
5	EVA	mask AP	55	—	Unverified
6	Mask Frozen-DETR	mask AP	54.9	—	Unverified
7	MasK DINO (SwinL, multi-scale)	mask AP	54.5	—	Unverified
8	ViT-Adapter-L (HTC++, BEiTv2, O365, multi-scale)	mask AP	54.2	—	Unverified
9	GLEE-Pro	mask AP	54.2	—	Unverified
10	SwinV2-G (HTC++)	mask AP	53.7	—	Unverified